AI Workshop: Hands-on with GANs Using Dense Neural Networks

Offered By: LinkedIn Learning

Tags

Data Visualization Courses Machine Learning Courses Deep Learning Courses Python Courses Neural Networks Courses TensorFlow Courses PyTorch Courses Generative Modeling Courses

Course Description

Overview

Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only!

Learn how to build and train generative adversarial networks (GANs) using dense neural networks in this interactive, workshop-style coding course.

Syllabus

Introduction

Understanding generative modeling

1. Introducing Generative Adversarial Networks

Course outline and prerequisites
Set up the virtual environment and run the notebook server
Introducing generative adversarial networks (GANs)
Instantiating the dataset and data loader
Viewing training data

2. Stand-Alone Training of Adversaries

Big picture overview of a GAN
Training the adversaries
The generator architecture and discriminator architecture
Understanding the generator and discriminator outputs
Stand-alone training of discriminator as classification model
Stand-alone training of generator

3. Training Generative Adversarial Networks

Computing losses for generator and discriminator
Understanding the minimax loss function
Setting up GAN training
Visualizing GAN training results
Problems with GANs and potential mitigations

Conclusion

Summary and next steps

Taught by

Janani Ravi

Related Courses

Neural Networks for Machine Learning
University of Toronto via Coursera Good Brain, Bad Brain: Basics
University of Birmingham via FutureLearn Statistical Learning with R
Stanford University via edX Machine Learning 1—Supervised Learning
Brown University via Udacity Fundamentals of Neuroscience, Part 2: Neurons and Networks
Harvard University via edX